The overall objective of the experiments proposed in this application is to enhance the quantitative assessment of coronary obstructions by applying sophisticated image processing techniques to coronary arteriographic images. Specifically, our goal is to improve the relationship between the arteriographic estimation of the degree of coronary obstruction and the physiological significance of the obstruction. We plan to pursue this goal by employing three complementary image processing techniques: 1) image enhancement techniques designed to assist visual edge detection; 2) automated edge detection techniques; and 3) non-geometric videodensitometric analysis of arteriograms to estimate luminal volume. The investigations will be performed in model systems and in patients. The image processing techniques will be performed in the University of Iowa Cardiovascular Image Processing Laboratory, a major multi-disciplinary image processing facility. A major strength of our proposal is our ability to compare the data obtained from image analyses with direct physiological measurements of the functional significance of individual obstructive coronary lesions in patients. The latter will be accomplished by utilizing intraoperative measurements of coronary reactive hyperemia with a unique Doppler probe developed and evalidated at the University of Iowa. The results achieved in our studies should be applicable to other approaches to obtaining the primary angiographic data, i.e., digital subtraction angiography or contrast enhanced computer tomography. Our ability to reach our goals is enhanced by a research environment fostering effective collaboration between coronary physiologists, computer engineers, cardiologists, and cardiovascular surgeons.